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Gemini 4 Argon

https://deepmind.google/models/gemini/
155•737max•30m ago•126 comments

Apple HomeView

https://www.apple.com/apple-homeview/
375•etothet•3h ago•460 comments

Thunderbird for iOS

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68•mjorgers•1h ago•17 comments

11 year old unsoundness bugs found in Rust borrow checker

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493•formerly_proven•6h ago•280 comments

We turned EmbeddingGemma 2 into a speech-to-text model

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283•amrrs•5h ago•64 comments

A Dynamic and Distributed Virtual GPU Cloud Built on Idle Apple Silicon Devices

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156•acossta•4h ago•62 comments

New Apple TV 4K

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113•corvad•3h ago•202 comments

I posted to HN, and then my website was flooded with AI bot traffic

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44•sammy0910•1h ago•24 comments

Launch HN: Consus (YC F24) – LLM gateway for companies handling sensitive data

11•ericmags•52m ago•4 comments

Show HN: Use your OpenAI subscription to create audiobooks

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128•janpmz•6h ago•63 comments

BB(10) > Graham's Number

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48•surprisetalk•3h ago•20 comments

A Visual Intro to Complex Numbers

https://photonlines.substack.com/p/a-visual-intro-to-complex-numbers
67•surprisetalk•4h ago•44 comments

Hittite royal archive found in Turkey

https://www.thehistoryblog.com/archives/77107
261•benbreen•10h ago•68 comments

Worlds More Habitable Than Earth? They're Out There

https://www.nytimes.com/2026/10/13/science/inhabitable-planets-solar-system.html
14•cainxinth•4h ago•19 comments

AI is a tool and using it well takes skill

https://yyhh.org/blog/2026/10/ai-is-a-tool/
563•layer8•18h ago•451 comments

Character.ai has initiated voluntary Chapter 11 bankruptcy

https://blog.character.ai/an-update-on-character-ai/
148•nryoo•9h ago•83 comments

How to engineer an AI harness for game development

https://kylekukshtel.com/ai-harness-engineering-game-development-claude-code
11•kkukshtel•2h ago•2 comments

CFTC Staff Were Told to Retract Analysis of Suspicious Oil Trades

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357•helsinkiandrew•6h ago•172 comments

Mozilla Introduces Firefox Enterprise

https://www.firefox.com/en-US/enterprise/
323•recvonline•4h ago•151 comments

GLM-Legal

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646•ilreb•1d ago•352 comments

The baffling intelligence of a single cell (2024)

https://jsomers.net/e-coli-chemotaxis/
370•jsomers•2d ago•115 comments

Hackers activate automatic defrosting in supermarket fridges across Europe

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836•Zeekaas•1d ago•944 comments

The United Kingdom Generates Less Electricity per Person Than in the 1970s

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25•karakoram•1h ago•3 comments

Intel D270 GPU AI Accelerator–Up to 480 GB LPDDR5X

https://www.intel.com/content/www/us/en/products/details/discrete-gpus/data-center-gpu/d-series.html
290•hurricanepootis•18h ago•161 comments

A Modern Web App in C

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669•prophittcorey•1d ago•289 comments

Document Review with Unsiloed and TypeSafe Jev

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38•ritzaco•8h ago•7 comments

A Book That Will Never Be Read

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32•jruohonen•2h ago•10 comments

Janas: Run LLMs larger than RAM by streaming experts from SSD

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205•khalidkhair•18h ago•74 comments

Making big downloads resumable in Firefox

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266•speckx•20h ago•125 comments

Who is vfmaddrnd231pd?

https://purplesyringa.moe/blog/who-is-vfmaddrnd231pd/
243•pngmangi•19h ago•21 comments
Open in hackernews

Launch HN: Consus (YC F24) – LLM gateway for companies handling sensitive data

9•ericmags•52m ago
Hey Hacker News! I'm Eric, the founder of Consus. We route all AI requests to ITAR restricted and controlled unclassified information (CUI) compliant infrastructure. Consus itself satisfies ITAR restrictions, and we recently completed our FedRAMP equivalency audit against the 410 FedRAMP High controls. FedRAMP High is the U.S. government’s strictest security baseline for cloud services handling sensitive unclassified data. A breach of this data could cause severe or catastrophic harm. Achieving FedRAMP equivalency, or authorization, is required before processing CUI information.

Demo: https://youtu.be/6MYxJe6P4oY

Aerospace and defense is experiencing rapid growth. Unfortunately, most companies are struggling to use AI because of necessary data protections & compliance risk. These companies can move even faster if they could use the AI tools that most other industries take for granted.

I spent most of my career prior to Consus in aerospace & defense. I launched national security payloads at SpaceX, and was an early employee at Castelion. I’ve watched first hand how compliance red-tape makes it difficult for companies to adopt new technologies and trust vendors that touch their sensitive data. For example, I worked with a satellite manufacturer that doesn’t allow any AI tools, even for non-sensitive work.

Even as AI has become extremely useful over the past 9-12 months, I was surprised by how many aerospace & defense companies refused to touch it. They could see how it could be helpful, but they were scared about model providers training on their data, violating an ITAR rule, or risk losing new business because of a failed cyber assessment. These are all rational fears.

There were a lot of ways to solve some/all of these problems, but we focused on building a compliant AI inference layer that can "plug" into any AI tool or workflow. Just as OpenRouter integrates with most tools, Consus can connect to tools like ChatGPT or Claude, open source tools including the Pi coding agent or Open WebUI, or integrate with applications built and maintained by individual organizations.

Almost no aerospace & defense company lives in all three major GovClouds (AWS, Azure, Google). When I mapped where frontier models can legally run for ITAR and CUI work, each provider had some subset of models, and each model achieved varying levels of compliance. Our customers don’t think in terms of cloud providers. They think about the data controls they require, and the model they want to use. That is why we built the compliance suffix. Under the hood, every request hits a single OpenAI-compatible endpoint, where keys are verified and policy is enforced before anything touches inference. Every model name must carry a compliance suffix, such as gpt-5.6-sol:fedramp-high or claude-opus-5-5:itar, and any bare model name is rejected. We never proxy to the standard commercial endpoints.

Our customers are also able to build an allowlist of models, and assign spend & model restrictions to individual users in the organization. This is all handled through our Consus Portal where teams can manage spend, keys, and policies.

A typical question we hear is why not just use Bedrock in AWS GovCloud or Azure Government directly. For small teams, just getting access to these platforms is difficult. For larger organizations, GovCloud lets you inherit some but not all of the controls needed to handle sensitive data. Also, models are split across providers: GPT-5.6 Sol is only available in Azure Government, while Claude Opus 5.5 is served through Bedrock in AWS GovCloud. If you want both, you are standing up and securing two separate government cloud environments. We run all of them behind one endpoint so customers don’t have to pick a cloud, and we handle the compliance work for each one.

Given the data sensitivities, Consus does not store any customer data at rest. All prompts and completions stay in memory only for the length of the request and are never logged or written to disk. Zero data retention is strictly enforced both on ourselves and the infrastructure/model providers. We do keep metadata on each request and response for billing and audit purposes.

Consus is not self-serve by design. ITAR requires us to know exactly who is on the other end of every key, so we verify every organization and put a contract in place before issuing API keys. We charge our customers a compliance fee starting at $40/mo/seat plus AI tokens at cost.

We are actively serving customers, and would love any feedback from security experts, or developers/engineers working in highly regulated industries!

References: API Documentation: https://gateway.consus.io/overview Security & Architecture: https://gateway.consus.io/security Compliance Details: https://consus.io/compliance

Comments

rahibali•41m ago
The compliance-suffix routing is a clean design choice — policy enforced in the API contract instead of buried in dashboard config. The hard part of any "zero data retention" gateway is observability, though: prompts routinely leak into error logs, APM traces, and dead-letter queues even when the happy path retains nothing. I'd want to know how redaction is handled there, because a single unredacted exception in a third-party error tracker can quietly undo the whole compliance story.
ericmags•13m ago
Glad you like the compliance suffix.

W.r.t observability: We don't use any third-party error tracker, APM, or queues. If any request fails, the client gets an error message that we write as opposed to the raw provider error. On our side, every log lives inside our boundary, and is written from a field allowlist (ids, model, token counts, status, latency). The JSON is purposely stripped away so any details in the request do not land in our logs.

runamuck•29m ago
I love this. Will this guarantee that proprietary/ sensitive/ CUI data won't leak to model training or other parties?
ericmags•22m ago
Correct. We have contractual agreements to ensure no data that passes through our platform will be used for model training purposes. In addition, we have in our contracts that we (Consus) will also not use any data for training purposes. We couldn't if we wanted to since we do not store any prompt data.